Abstract: A method and a system for vehicle-to-pedestrian collision avoidance system, the system comprising participants consisting of Long-Term Evolution (LTE)-capable user equipment (UE) terminals physically linked to at least one vehicle and at least one pedestrian; wherein a spatiotemporal positioning of the terminals is determined from Long Term Evolution (LTE) cellular radio signals mediated by Long-Term Evolution (LTE) cellular base stations (BS) and a Location Service Client (LCS) server including an embedded Artificial Intelligence algorithm comprising a Recurrent Neural Network (RNN) algorithm and analyzes the spatiotemporal positioning of the terminals and determines the likely future trajectory and communicates the likely future trajectory of the participants to the terminals physically linked to the pedestrian; the terminals physically linked to the pedestrian include an embedded Artificial Intelligence algorithm comprising a Conditional Random Fields (CRFs) algorithm to determine if the likely future traj

Abstract: A distributed method and system for collision avoidance between vulnerable road users (VRUs) and vehicles is provided. The method and system provide for pedestrian-to-vehicle (P2V) collision avoidance, in the field of intelligent transportation technology and data analytics with an artificial intelligence (AI) algorithm distributed among edge and cloud systems. The distribution of data analytics is weighted between edge and cloud systems: the cloud system referring to a Neural Network computational algorithm embedded in a distant server, and the edge system referring to a user equipment (UE) mobile terminal having a P2V collision avoidance applicative algorithm. The described technology can provide P2V danger notifications relating to the field of road safety, and pertaining to collision avoidance, before accidents happen.

Abstract: This application relates to a method and a system for automatically detecting jaywalking of vulnerable road users (VRUs). In one aspect, the method includes first determining whether a detected current trajectory of the first VRU substantially matches a first path infrequently taken by the plurality of VRUs. The method also includes second determining whether a predicted trajectory of a selected VRU crosses a second path frequently taken by a plurality of vehicles based on the past trajectory data of the plurality of vehicles. The method further includes third determining whether the predicted trajectory of the selected VRU is substantially distal to a third path marked for VRU use. The method further includes determining whether the selected VRU is jaywalking based on the first determining, the second determining, and the third determining.

Abstract: This application relates to a method and a system for automatically detecting jaywalking of vulnerable road users (VRUs). In one aspect, the method includes first determining whether a detected current trajectory of the first VRU substantially matches a first path infrequently taken by the plurality of VRUs. The method also includes second determining whether a predicted trajectory of a selected VRU crosses a second path frequently taken by a plurality of vehicles based on the past trajectory data of the plurality of vehicles. The method further includes third determining whether the predicted trajectory of the selected VRU is substantially distal to a third path marked for VRU use. The method further includes determining whether the selected VRU is jaywalking based on the first determining, the second determining, and the third determining.

Abstract: Methods and systems for collision avoidance between vulnerable road users (VRUs) and vehicles are provided. In one aspect, a method and a system for collision avoidance between vulnerable road users (VRUs) and vehicles based on emitted signal relates to VRUs and vehicles configured to emit and receive a proximity signal pertaining to road usage safety before accidents happen. The method and the system for pedestrian-to-vehicle (P2V) collision avoidance is based on emitted signal at the edge. The usefulness of the method and the system is for providing danger notifications pertaining to the field of road safety, and pertaining to collision avoidance, before accidents happen. The method and the system further relate to precautious collision avoidance notifications using past, current and predicted trajectories of VRUs and vehicles, based on emitted signal at the edge.

Abstract: This application relates to a method and a system for automatically detecting jaywalking of vulnerable road users (VRUs). In one aspect, the method includes first determining whether a detected current trajectory of the first VRU substantially matches a first path infrequently taken by the plurality of VRUs. The method also includes second determining whether a predicted trajectory of a selected VRU crosses a second path frequently taken by a plurality of vehicles based on the past trajectory data of the plurality of vehicles. The method further includes third determining whether the predicted trajectory of the selected VRU is substantially distal to a third path marked for VRU use. The method further includes determining whether the selected VRU is jaywalking based on the first determining, the second determining, and the third determining.

Abstract: Provided are a method and a system for collision avoidance between vulnerable road users (VRUs) and vehicles, notably for pedestrian-to-vehicle (P2V) collision avoidance, in the field of intelligent transportation technology and data analytics distributed among edge and cloud systems. In one aspect, the method and the system for collision avoidance between VRUs and vehicles is further based on a reflected optical signal, wherein VRUs and vehicles are configured to emit and receive a proximity signal pertaining to road usage safety before accidents happen. The method and the system for pedestrian-to-vehicle (P2V) collision avoidance is further based on a reflected optical signal analysis at the edge. The method and system are useful for providing danger notifications pertaining to the field of road safety, and pertaining to collision avoidance before accidents happen.

Abstract: A method and a system for vehicle-to-pedestrian collision avoidance system, the system comprising participants consisting of Long-Term Evolution (LTE)-capable user equipment (UE) terminals physically linked to at least one vehicle and at least one pedestrian; wherein a spatiotemporal positioning of the terminals is determined from Long Term Evolution (LTE) cellular radio signals mediated by Long-Term Evolution (LTE) cellular base stations (BS) and a Location Service Client (LCS) server including an embedded Artificial Intelligence algorithm comprising a Recurrent Neural Network (RNN) algorithm and analyzes the spatiotemporal positioning of the terminals and determines the likely future trajectory and communicates the likely future trajectory of the participants to the terminals physically linked to the pedestrian; the terminals physically linked to the pedestrian include an embedded Artificial Intelligence algorithm comprising a Conditional Random Fields (CRFs) algorithm to determine if the likely future traj

Abstract: A method and a system for vehicle-to-pedestrian collision avoidance system, the system comprising participants consisting of Long-Term Evolution (LTE)-capable user equipment (UE) terminals physically linked to at least one vehicle and at least one pedestrian; wherein a spatiotemporal positioning of the terminals is determined from Long Term Evolution (LTE) cellular radio signals mediated by Long-Term Evolution (LTE) cellular base stations (BS) and a Location Service Client (LCS) server including an embedded Artificial Intelligence algorithm comprising a Recurrent Neural Network (RNN) algorithm and analyzes the spatiotemporal positioning of the terminals and determines the likely future trajectory and communicates the likely future trajectory of the participants to the terminals physically linked to the pedestrian; the terminals physically linked to the pedestrian include an embedded Artificial Intelligence algorithm comprising a Conditional Random Fields (CRFs) algorithm to determine if the likely future traj

Abstract: A method and a system for vehicle-to-pedestrian collision avoidance system, the system comprising participants consisting of Long-Term Evolution (LTE)-capable user equipment (UE) terminals physically linked to at least one vehicle and at least one pedestrian; wherein a spatiotemporal positioning of the terminals is determined from Long Term Evolution (LTE) cellular radio signals mediated by Long-Term Evolution (LTE) cellular base stations (BS) and a Location Service Client (LCS) server including an embedded Artificial Intelligence algorithm comprising a Recurrent Neural Network (RNN) algorithm and analyzes the spatiotemporal positioning of the terminals and determines the likely future trajectory and communicates the likely future trajectory of the participants to the terminals physically linked to the pedestrian; the terminals physically linked to the pedestrian include an embedded Artificial Intelligence algorithm comprising a Conditional Random Fields (CRFs) algorithm to determine if the likely future traj

Abstract: Provided are a method and a system for collision avoidance between vulnerable road users (VRUs) and vehicles, notably for pedestrian-to-vehicle (P2V) collision avoidance, in the field of intelligent transportation technology and data analytics distributed among edge and cloud systems. In one aspect, the method and the system for collision avoidance between VRUs and vehicles is further based on a reflected optical signal, wherein VRUs and vehicles are configured to emit and receive a proximity signal pertaining to road usage safety before accidents happen. The method and the system for pedestrian-to-vehicle (P2V) collision avoidance is further based on a reflected optical signal analysis at the edge. The method and system are useful for providing danger notifications pertaining to the field of road safety, and pertaining to collision avoidance before accidents happen.

Abstract: Methods and systems for collision avoidance between vulnerable road users (VRUs) and vehicles are provided. In one aspect, a method and a system for collision avoidance between vulnerable road users (VRUs) and vehicles based on emitted signal relates to VRUs and vehicles configured to emit and receive a proximity signal pertaining to road usage safety before accidents happen. The method and the system for pedestrian-to-vehicle (P2V) collision avoidance is based on emitted signal at the edge. The usefulness of the method and the system is for providing danger notifications pertaining to the field of road safety, and pertaining to collision avoidance, before accidents happen. The method and the system further relate to precautions collision avoidance notifications using past, current and predicted trajectories of VRUs and vehicles, based on emitted signal at the edge.

Abstract: Provided are a method and a system for collision avoidance between vulnerable road users (VRUs) and vehicles, notably for pedestrian-to-vehicle (P2V) collision avoidance, in the field of intelligent transportation technology and data analytics distributed among edge and cloud systems. In one aspect, the method and the system for collision avoidance between VRUs and vehicles is further based on a reflected optical signal, wherein VRUs and vehicles are configured to emit and receive a proximity signal pertaining to road usage safety before accidents happen. The method and the system for pedestrian-to-vehicle (P2V) collision avoidance is further based on a reflected optical signal analysis at the edge. The method and system are useful for providing danger notifications pertaining to the field of road safety, and pertaining to collision avoidance before accidents happen.

Abstract: Methods and systems for collision avoidance between vulnerable road users (VRUs) and vehicles are provided. In one aspect, a method and a system for collision avoidance between vulnerable road users (VRUs) and vehicles based on emitted signal relates to VRUs and vehicles configured to emit and receive a proximity signal pertaining to road usage safety before accidents happen. The method and the system for pedestrian-to-vehicle (P2V) collision avoidance is based on emitted signal at the edge. The usefulness of the method and the system is for providing danger notifications pertaining to the field of road safety, and pertaining to collision avoidance, before accidents happen. The method and the system further relate to precautious collision avoidance notifications using past, current and predicted trajectories of VRUs and vehicles, based on emitted signal at the edge.